1. Technical Field
The present invention relates generally to an improved data processing system. In particular, the present invention provides a method and apparatus for obtaining performance data in a data processing system. Still more particularly, the present invention provides a method and apparatus for hardware assistance to software tools in obtaining performance data in a data processing system.
2. Description of Related Art
In analyzing and enhancing performance of a data processing system and the applications executing within the data processing system, it is helpful to know which software modules within a data processing system are using system resources. Effective management and enhancement of data processing systems requires knowing how and when various system resources are being used. Performance tools are used to monitor and examine a data processing system to determine resource consumption as various software applications are executing within the data processing system. For example, a performance tool may identify the most frequently executed modules and instructions in a data processing system, or may identify those modules which allocate the largest amount of memory or perform the most I/O requests. Hardware performance tools may be built into the system or added at a later point in time.
One known software performance tool is a trace tool. A trace tool may use more than one technique to provide trace information that indicates execution flows for an executing program. A trace contains data about the execution of code. For example, a trace may contain records about events generated during the execution of the code. A trace may include information, such as a process identifier, a thread identifier, and a program counter. The information in a trace may vary depending on a particular profiling or analysis that is to be performed. A record is a unit of information relating to an event.
One technique keeps track of particular sequences of instructions by logging certain events as they occur, a so-called event-based profiling technique. For example, a trace tool may log every entry into, and every exit from, a module, subroutine, method, function, or system component. Alternately, a trace tool may log the requestor and the amounts of memory allocated for each memory allocation request. Typically, a time-stamped record is produced for each such event. Corresponding pairs of records, similar to entry-exit records, also are used to trace execution of arbitrary code segments, starting and completing I/O or data transmission, and for many other events of interest.
In order to improve performance of code generated by various families of computers, it is often necessary to determine where time is being spent by the processor in executing code, such efforts being commonly known in the computer processing arts as locating “hot spots”. Ideally, one would like to isolate such hot spots at the instruction and/or source line of code level in order to focus attention on areas which might benefit most from improvements to the code.
Another trace technique involves periodically sampling a program's execution flows to identify certain locations in the program in which the program appears to spend large amounts of time. This technique is based on the idea of periodically interrupting the application or data processing system execution at regular intervals, so-called sample-based profiling. At each interruption, information is recorded for a predetermined length of time or for a predetermined number of events of interest. For example, the program counter of the currently executing thread, which is an executable portion of the larger program being profiled, may be recorded during the intervals. These values may be resolved against a load map and symbol table information for the data processing system at post-processing time, and a profile of where the time is being spent may be obtained from this analysis.
With time profiling performance analysis, support for dynamic loading and unloading of modules and just-in-time (JIT) compiled methods typically uses tracing with time stamps. Time profiling is also referred to as “tprof”. The time stamps are used to allow for playing back the trace to repeat the history of load information to allow for the dynamic resolution of address to name. This resolution is especially important for JIT. However, a tprof trace containing time stamps may require large memory resources to hold and analyze the trace.
Other solutions that are currently available avoid using any time stamps. Instead of using time stamps, these types of solutions write out address mapping when a module unload occurs. This approach requires a real time consumption of the information, which can significantly affect performance in a data processing system.
Thus, it would be advantageous to have an improved method, apparatus, and computer instructions for generating trace data during time profiling analysis in a manner that reduces or compresses the amount of trace data generated.